OBJECTIVE:
We assessed the factors associated with dyslipidemia in children and adolescents
enrolled in the public school system of the city of Salvador, Bahia.METHODS:
All participants were submitted to anthropometric evaluation and to cholesterol
and triglyceride blood tests. Data related to food intake, physical activity and
family socioeconomic and housing conditions were obtained from parents or guardians.
Data were analyzed using multivariate logistic regression.RESULTS:
The prevalence of dyslipidemia was 25.5% (IC:95% 22.7; 28.3). We observed a significant
positive association between dyslipidemia and the following factors: overweight
(OR = 3.40, 95% CI 2.07 to 5.58), moderate and high intake of risk food (OR =
1.49, 95%: 1.01 to 2.19), low and moderate intake of protective foods (OR = 1.54,
95% CI 1.05 to 2.26) and lower maternal level of schooling (OR = 1.72, 95%: 1.05
to 2.26).CONCLUSION: Overweight, inadequate food intake and low maternal
level of schooling were factors associated with dyslipidemia.

Experts
have warned about the increase in dyslipidemia in children and adolescents. In
Brazil, there are no national epidemiological data on the prevalence of this disease
that cover the entire country. However, specific studies have shown high prevalences
of dyslipidemia in children and adolescents, varying between 3.1% and 46.5%, in
some regions of this country1-10.

Some
studies have been performed to assess factors associated with dyslipidemia3-7.
These studies argue that, in the majority of cases, the risk of dyslipidemia is
associated with excessive weight. Specialists have emphasized that the trend towards
the increase in the proportion of overweight and obesity - such as what has occurred
in developed countries - has led to metabolic changes in lipid profile11.
The occurrence of overweight and obesity, in their turn, depends on a series of
environmental factors associated with lifestyle, among which physical inactivity
and negative changes in eating habits are included12,13. However, it
is not possible to disregard the role of maternal level of education in the adoption
of healthy behavior, which may thus influence the magnitude of occurrence of this
health problem14.

Many
studies have indicated an association between dyslipidemia and the occurrence
of non-communicable chronic diseases (NCCD), especially circulatory system diseases
(CSD). Among CSDs, cerebrovascular diseases and ischemic heart diseases stand
out, as they totaled more than 47% of CSD deaths in Brazil, in 200415.
Thus, the identification of factors that lead to dyslipidemia can contribute to
the development of preventive health programs, aiming at lifestyle changes and
health promotion, and thus preventing thousands of adolescents from prematurely
developing coronary artery disease.

In
view of this situation, the present study was conducted to assess factors associated
with dyslipidemia in children and adolescents enrolled in the public school network
of the city of Salvador, BA, Brazil.

Methods

Study
design/population/sample

A
cross-sectional study was conducted with students of both sexes aged between seven
and 14 years. These students had been identified in a previous broader investigation
that aimed to analyze factors associated with iron-deficiency anemia in children
and adolescents enrolled in the public school network of the city of Salvador16.

The
sampling process of the original study involved a complex design, with the stratification
of schools on two levels (state and municipal), followed by three-stage cluster
sampling, described as follows: the first stage is represented by health districts;
the second, schools; and the third, students. Due to field logistics issues, information
about the students selected were obtained from six out of the 12 districts existing
in Salvador, where there were 117 state schools (corresponding to 53.9% of all
schools) and 173 municipal schools (corresponding to 48.8% of all schools). State
schools included 58,059 students, while municipal schools included 56,555 students.
A total of ten students from each of the 58 municipal schools and 23 students
from each of the 27 state schools were needed to meet the previously defined sample
size, totaling 1,200 students. Of all these initially selected, 937 children and
adolescents of both sexes, aged between seven and 14 years, participated in the
present study. Considering the objective pursued by this study and the fact that
this sample was not estimated, an a posteriori sample error was calculated. Under
these circumstances, there was a posteriori error of 2.8% to detect a prevalence
of dyslipidemia of 25.5%, with a confidence level of 95%.

Dependent
variable

Dyslipidemia
- cholesterol level and triglyceride level

An
Accutrend® CGT portable monitor (Roche Diagnostics) was used to determine
total cholesterol and triglyceride levels, adopting a reflectance photometry method.
Calibration was automatic and performed in children and adolescents, using a Code
Strip that follows each flask with reagent strips. The product code is 40000486
and it is manufactured by Roche Diagnostics GMBH, a German company registered
with the Brazilian Health Ministry under number 12016400350.

The
reference values used to diagnose hypercholesterolemia and hypertriglyceridemia
in children and adolescents were recommended by the I Diretriz de Prevenção
da Aterosclerose na Infância and Adolescência (1st
Guidelines for Atherosclerosis Prevention in Childhood and Adolescence) of the
Sociedade Brasileira de Cardiologia ( Brazilian Heart Society)17.
Individuals who showed an increased value in at least one of the following tests
were considered to be dyslipidemic: Cholesterol > 170 (mg/dl) and/or
Triglycerides > 130 (mg/dl).

Independent
variables

Physical
activity level

The
physical activity level was assessed using the Previous Day Physical Activity
Recall (PDPAR). This questionnaire was developed by Russell R. Pate of the University
of South Carolina, USA, and translated and modified by M.V. Nahas of the Núcleo
de Pesquisa em Atividade Física e Saúde (Physical Activity and
Health Research Center) of the Universidade Federal de Santa Catarina (SUÑÉ,
2007)(18). This questionnaire provides information about the intensity
and time spent on physical activities. The final PDPAR score is subsequently obtained
from these values by multiplying the intensity coefficient (3, 2 or 1 for intense,
moderate or mild, respectively) by the exercise duration coefficient (1, 2 and
3 for <15', 15-30' and >30', respectively). In the present study, the score
obtained was distributed into tertiles: 1st tertile (0 to 5 points),
2nd tertile (6 to 12 points) and 3rd tertile (>
13 pointsReference category).

Anthropometric
state

Anthropometric
measurements were collected in the school in a standardized manner, following
the procedures recommended by the Anthropometric Standardization Reference Manual
(LOHMAN et al., 1988)19. Weight was obtained with the help of the Marte
microelectronic scale, model PP 200-50, with a capacity of 199.95 kg and accuracy
of 50 grams. The Leicester Height Measure stadiometer, divided into tenths of
centimeters, was used to measure height. The anthropometric data collection procedure
recommended by Lohman et al (1988)19 was adopted.

Participants'
age was recorded from the information of the Municipal and City Departments of
Education. Age was confirmed by checking the birth certificate or identity card
during interview.

Anthropometric
measurements were collected (weight and height) to calculate body mass index (BMI).
The World Health Organization percentile tables (2007)20 were used
as framework to assess the anthropometric state, according to age (between two
and 20 years) and sex. The WHO proposal (2006)21 was used for classification:
low weight (< percentile 3), eutrophia (> percentile 3 and < percentile
85Reference category), overweight (> percentile 85 and
< percentile 97), and obesity (> percentile 97). The overweight
and obesity categories were grouped together for the analysis. Thus, overweight
individuals had a BMI value > percentile 85.

Food
intake

The
Quantitative Food Frequency Questionnaire (FFQ) developed by Slater et al.22
was used to assess food intake frequency. This instrument was validated by Voci
et al23. There were 132 food items in the FFQ, with the inclusion of
regional foods. Each food item in the FFQ included intake frequency categories,
ranging from "never" (lack of intake) to "daily", and the number of times such
food items were consumed on the day, ranging from "once" to "six times/day". Food
items were distributed into two groups, according to their recognized role in
the development of risk factors for Cardiovascular Diseases24,25. The
inclusion criterion for each food in the group was the fact that at least 70%
of participants reported the intake of such foods.

Group
2: comprised by foods considered to be protective against the development of dyslipidemia:
fruits; vegetables; legumes; roots; cereals and derivatives (rice, bread, crackers
and flours).

Food
intake assessment was performed according to the methodology proposed by Fornés
et al (2002)25, which adopts a daily intake equivalent to 30 days in
the month (monthly intake) as framework. Thus, a certain weight value was attributed
to each intake frequency category, based on the monthly frequency. In addition,
the daily intake of food items corresponds to the maximum weight value (weight
1). The remaining weight values were obtained according to the following equation:

Weight
= (1/30) [(a+b)/2]

Where
"a" and "b" represent the numerical interval of monthly intake frequency. As the
majority of possibilities of food frequency responses reflect the weekly intake,
the number of weekly responses was converted into monthly intake. Considering
the fact that one month has four weeks, the weekly intake was multiplied by four,
thus obtaining the monthly intake frequency. An intake frequency score was attributed
to each food consumed by participants. Subsequently, these variables were distributed
into tertiles. Group 1 was categorized accordingly: 1st tertile - low
intakeReference category; 2nd tertile - moderate intake;
3rd tertile - high intake. Group 2 was categorized accordingly: 1st
tertile - low intake; 2nd tertile - moderate intake; 3rd
tertile - high intakeReference category.

Data
on housing characteristics (home ownership conditions, type of construction, primary
flooring material, primary roof material and part of the home, number of residents
per room) and basic sanitation (water supply, garbage collection and sewage system)
to construct an index adapted to the model proposed by Issler & Giugliani
(1997)26. A score was given to each situation, 0 being the most
favorable and 1 being the most unfavorable. The sum of these values characterizes
the housing and environmental condition index, categorized into two strata: adequate
(score < 04 Reference category) and inadequate (score >
04).

In
addition, data on maternal level of education were collected (proxy indicator
of household socioeconomic conditions). A total of three levels were considered
for this variable, according to the school grades: level 1 - until the 4th
grade; level 2 - between the 5th and 8th grades; and level
3 - secondary and higher educationReference category.

Ethical
questions/issues

The
study protocol was submitted to the Universidade Federal da Bahia (Bahia
Federal University) Collective Health Institute Research Ethics Committee, which
assessed and approved it according to its ethical relevance.

Data
analysis

The
variables that showed a p value < 0.30 in the univariate analysis were
selected, according to the criterion suggested by Hosmer & Lemeshow (1989)27.
Subsequently, multivariate analysis was performed using the logistic regression
technique. The magnitude of association between associated factors and the occurrence
of dyslipidemia was described in Odds Ratios (OR) and respective 95% confidence
intervals (95%CI). Variables with a p value < 0.05 remained in the adjusted
model.

Statistical
analyses were corrected by the complex sampling design, using the set of STATA's
SVY commands (version 9.0).

Results

Of
all 1,200 initially selected students, there were 69 losses (5.75 %), resulting
in a sample with 1,131 participants. These losses occurred due to refusals, children
moving to other cities, or their being transferred to other schools. Of all these,
194 students were excluded due to the lack of lipidogram records. Consequently,
the sample that was effectively studied was comprised of 937 children and adolescents
of both sexes, aged between seven and 14 years.

It
should be emphasized that there were no statistically significant differences
between the socioeconomic, anthropometric and demographic characteristics of the
original sample and those of the sub-sample used in this study (data not shown).

The
prevalence of dyslipidemia was estimated to be 25.5% (95%CI 22.7; 28.3) (adolescents
had at least one of the disorders studied). Of all 937 children and adolescents,
49.9% of participants were females and the majority of them were aged between
ten and 14 years (86.0%). With regard to socioeconomic conditions, 32.9% lived
under inadequate housing conditions and 32.6% of mothers had completed the 4th
grade of primary school. Physical inactivity was frequent in 27.6% of children
and the intake of foods considered to be moderate and high risk for dyslipidemia
was 67.5%, a prevalence that was slightly higher than that observed for low and
moderate intake of protective foods (62.9%). The occurrence of overweight/obesity
was identified in 12.4% of participants (Table 1).

The
results of the univariate analysis indicate a statistically significant positive
association between dyslipidemia and anthropometric status (p<0.001) and a
borderline significance level for the frequency of intake of the protective foods
selected (p=0.051). There were no statistically significant associations for the
remaining variables studied (p<0.051) (Table
2).

The
prevalence of dyslipidemia found in the present study (25.5%) is lower than that
reported by Franca and Alves (2006) in Recife/PE (29.7%)7 and by Moura
et al (2000) in Campinas/SP (35%)9. However, it is in agreement with
that observed by Giuliano et al (2005)28 in Florianópolis/SC
(22.0%) and by Seki et al (2001) in Londrina/PR (20.8%)2. In addition,
this prevalence is higher than those found by Gerber & Zielinsky, (1997) in
Bento Gonçalves/RS, (10.33%)29 and by Grillo (2005) in Itajaí/SC
(4.7%)30. Regardless of the cut-off points used for such diagnosis
or even biochemical analysis techniques, the high prevalences of this event in
children and adolescents in several regions of Brazil should be emphasized.

Data
from the present study revealed the influence of excessive weight on the occurrence
of dyslipidemia (Table 3). In Brazil, there are still few studies
on the evaluation of factors that determine the development of dyslipidemia, such
as excessive weight in children and adolescents. Of all studies included in the
Brazilian literature, those conducted by Giuliano et al (2008)28, Coronelli
and Moura (2003)3 and Carvalho et al. (2007)8 should be
emphasized. The results of these studies may indicate the atherogenic role of
excessive weight in this life cycle, thus contributing to the occurrence of dyslipidemia.
According to some authors, dyslipidemia occurs mainly due to the development of
hyperinsulinism (resistance to insulin), which is initially peripheral and subsequently
systemic, among other mechanisms31. The evidence found indicates that
an adequate weight/height ratio improves the lipid profile and reduces cardiovascular
risks32.

Dyslipidemia
may be attributed to environmental factors associated with lifestyle, among which
inadequate eating habits and physical inactivity are particularly included. In
the present study, the negative influence of low and moderate intake of protective
foods (2nd and 3rd tertiles) and moderate and high intake
of high risk foods (2nd and 3rd tertiles) on the lipid status
of children and adolescents who participated in this study could be observed.
These intake patterns reflect the lifestyle changes experienced by children and
adolescents, which may be explained by the nutritional transition identified for
the Brazilian population in recent years12,13. These changes have promoted
an increase in the intake of manufactured foods, eating out habits and replacement
of traditional meals by snack foods. These changes lead to the intake of high
energy density food products, such as those rich in fat and simple carbohydrates,
to the detriment of sources of fibers, which are found in fruits and vegetables
and have fewer calories and more nutrients. It should be emphasized that the results
found in this study are in agreement with those that focus on the influence of
the traditional Brazilian diet (based on rice and beans) as protective of factors
associated with dyslipidemia33,34. The effects of soluble fibers on
serum lipid concentrations have been reported in several studies, both with animals
and human beings35. Results of these studies show that soluble fibers,
such as pectin (fruits) and vegetable gums (oat, barley and legumes - beans, chickpeas,
lentils and green peas), reduce gastrointestinal transit time and help to eliminate
cholesterol35 .

Results
of the present study indicated the influence of low level of education on lipid
profile changes due to excessive weight. Opportunities to improve one's level
of education and to access information usually promote a more adequate choice
of foods and, consequently, an improvement in the adequacy of anthropometric measurements.
The influence of maternal level of education on the occurrence of dyslipidemia
observed in this study could be suggesting, among other things, that mothers with
a higher level of education are more actively participating in child care, which
may result in a lower occurrence of dyslipidemia.

It
should be emphasized that the main limitation of this investigation is in the
fact that it had a cross-sectional design. This affects the interpretation of
results, in the sense that it is not possible to establish causal relationships
in this type of study, because it cannot indicate a temporal sequence between
exposure to the factor and the subsequent development of the disease. However,
the results found are compatible with those reported in the literature consulted.
Some of these derived from intervention studies, which show that an improvement
in eating habits and weight control are important aspects in dyslipidemia prevention,
among the risk factors associated with cardiovascular diseases(35), (36).
In the present study, the photometry method was used to determine cholesterol
and triglyceride levels, which could lead to a limitation due to classification
errors and underestimated diagnosis. However, reflectance photometry to determine
serum or plasma cholesterol and triglycerides has been currently used. Correlation
coefficients (r) higher than 0.90, observed between the photometric method and
laboratory methods, have promoted the use of the portable Accutrend® CGT
monitor in epidemiological studies(37).

Despite
these limitations, it could be concluded that dyslipidemia was associated with
low maternal level of education, low intake of protective foods, moderate and
high intake of high risk foods and excessive weight. It is possible that certain
lifestyle changes, such as the maintenance of a nutritionally adequate diet and
body weight control, among other aspects that include improvement in socioeconomic
conditions, are associated with a reduction in risk factors for coronary arterial
disease.